Abstract
We develop a field theory-inspired stochastic model for description of tumour growth based on an analogy with an SI epidemic model, where the susceptible individuals (S) would represent the healthy cells and the infected ones (I), the cancer cells. From this model, we obtain a curve describing the tumour volume as a function of time, which can be compared to available experimental data.
Highlights
In a recent letter [1], we have shown how the standard field theoretical language based on creation and annihilation operators may be used for a straightforward derivation of closed master equations [3] to describe the population dynamics of multivariate stochastic epidemic models
A single hamiltonian function sums up the dynamics compactly, even when births and deaths allow the population size to change, and it may be written down from a verbal description of the transitions presented in these models
We employ the very same methodology established in [1] to develop a field-theory inspired stochastic model for description of tumour growth based on an analogy with an SI epidemic model [5], where the
Summary
In a recent letter [1], we have shown how the standard field theoretical language based on creation and annihilation operators (building blocks of the second quantization method [2]) may be used for a straightforward derivation of closed master equations [3] to describe the population dynamics of multivariate stochastic epidemic models. This was mainly motivated by the observation that, as remarked in [4], for the kinds of model studied in population biology and epidemiology, a field theoretical description is notationally neater and more manageable than standard methods, in often replacing sets of equations with single equations with the same content.
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